l y <pligly <at> gmail.com> writes:
>
> Hi everyone, when I use the two sample Kolmogorov¨CSmirnov ks2Test like this:
> x=read.table("e:/x.txt")
> y=rstable(1000,alpha,beta,gamma,delta)
>
> I alway get results as follows:
> Warning messages:
[snip]
> Strangely,I got a total same result! I really want to know whether there are
> any other sources that could induce this result except for the continuity
> of distribution? If there are, what are they?
> Any help will be much appreciated!
>
> Lily
>
The problem is that you have ties in your *data* -- nothing
to do with the distribution you are testing against.
You could try adding a tiny bit of random noise to your
data and see if it makes any difference in the answers -- e.g.
ks.test(rnorm(length(x),mean=x,sd=0.0001),y)
Others may have better ideas.
Make sure to look at ?ks.test and read the paragraph
about ties carefully ...
Ben Bolker
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